Mapping and encoding gemological features

ABSTRACT

Embodiments of the present invention disclose a method, computer program product, and system for mapping one or more inclusions in a mineral crystal. A set of image data associated with the mineral crystal is receiving. The received set of image data is analyzed. One or more inclusions associated with the mineral crystal is identified based on the analyzed image data. The identified one or more inclusions of the mineral crystal are mapped to a tree structure representing the surface of the mineral crystal. The mapped one or more inclusions are encoded as a chain-code associated with the mineral crystal. A radial distance between a center of mass value of the mineral crystal and a center of mass value of the identified one or more inclusions is calculated and a mineral crystal fingerprint is generated.

BACKGROUND

The present invention relates generally to the field of gemologicalanalysis, and more particularly to mapping gemological features.

Many natural or manmade stones or mineral formations are usable as gems.Some examples include diamonds, emeralds, or rubies. A typical featureof a precious stone includes inclusions of other materials, for example,impurities, defects, or imperfections, in the precious stone. Forexample, diamonds may contain black carbon specs, emeralds may containstrands or specs of differently colored minerals, and other suchimpurities may comprise an inclusion. Cracks, chipped edges or corners,thickness or thinness of a cut or facet, and variations in refractiveindex are also examples of imperfections, or inclusions.

SUMMARY

Embodiments of the present invention disclose a method, computer programproduct, and system for mapping one or more inclusions in a mineralcrystal. A set of image data associated with the mineral crystal isreceiving. The received set of image data is analyzed, wherein analyzingthe received set of image data further comprises segmenting the imagedata via machine learned parameters. One or more inclusions associatedwith the mineral crystal is identified based on the analyzed image data,wherein inclusions are non-linear isolated regions on a surface of themineral crystal. The identified one or more inclusions of the mineralcrystal are mapped to a tree structure representing the surface of themineral crystal. The mapped one or more inclusions are encoded as achain-code associated with the mineral crystal. A radial distancebetween a center of mass value of the mineral crystal and a center ofmass value of the identified one or more inclusions is calculated and amineral crystal fingerprint is generated, wherein the mineral crystalfingerprint is based on at least the encoded one or more inclusions andthe calculated radial distance.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

FIG. 1 is a functional block diagram illustrating a distributed dataprocessing environment, in accordance with an embodiment of the presentinvention.

FIG. 2 depicts a functional block diagram illustrating the components ofan application within the distributed data processing environment, inaccordance with an embodiment of the present invention.

FIG. 3 is a flowchart depicting operational steps of a mappingapplication, on a server computer within the data processing environmentof FIG. 1, in accordance with an embodiment of the present invention.

FIG. 4 depicts an illustrative block flow diagram of the analysis,mapping, and encoding of image data in accordance with an embodiment ofthe present invention.

FIG. 5 depicts a block diagram of components of the server computerexecuting the inclusion mapping application, in accordance with anembodiment of the present invention.

FIG. 6 depicts an exemplary diagram of a Freeman's chain-code and anexemplary diagram of chain-coding.

DETAILED DESCRIPTION

Embodiments of the present invention relate to the field of computing,and more particularly to mapping and encoding gemological features. Thefollowing described exemplary embodiments provide a system, method, andprogram product to, among other things, mapping one or more inclusionsin a mineral crystal or diamond. Therefore, the present embodiment hasthe capacity to improve the technical field of diamond mapping andencoding by automatically generating diamond digital fingerprints inorder to, for example, make an appraisal for, or the tracking of,diamonds. To aid in appraisals and tracking of diamonds, it may beadvantageous to be able to identify inclusions and generate a digitalmap of the inclusions from various visual sources.

Detailed embodiments of the claimed structures and methods are disclosedherein; however, it can be understood that the disclosed embodiments aremerely illustrative of the claimed structures and methods that may beembodied in various forms. This invention may, however, be embodied inmany different forms and should not be construed as limited to theexemplary embodiments set forth herein. Rather, these exemplaryembodiments are provided so that this disclosure will be thorough andcomplete and will fully convey the scope of this invention to thoseskilled in the art. In the description, details of well-known featuresand techniques may be omitted to avoid unnecessarily obscuring thepresented embodiments.

References in the specification to “one embodiment”, “an embodiment”,“an example embodiment”, etc., indicate that the embodiment describedmay include a particular feature, structure, or characteristic, butevery embodiment may not necessarily include the particular feature,structure, or characteristic. Moreover, such phrases are not necessarilyreferring to the same embodiment. Further, when a particular feature,structure, or characteristic is described in connection with anembodiment, it is submitted that it is within the knowledge of oneskilled in the art to affect such feature, structure, or characteristicin connection with other embodiments whether or not explicitlydescribed.

Almost all diamonds have small imperfections visible on the surface.These imperfections are caused naturally as a diamond is formed underextreme pressure and heat. The size and amount of imperfections visibleon the surface of the diamond often determine the overall grade andmonetary value of the stone. This grading procedure is typically amanual process where a human grader inspects and maps out theimperfections of the diamond with the help of microscopes, and othertools, and contributes this to an overall quality grade. The claritygrade of a particular gemstone, such as a diamond, is predominantlydetermined by the size and quality of inclusions. Most typically,gemstones are assigned a grade based on a clarity scale: Flawless (FL),Internally Flawless (IF), Very Very Slightly Included (VVS1 VVS2), VerySlightly Included (VS1 VS2), Slightly Included (SI1 SI2), Included (I1I2 I3). As part of the grading process, the inclusions are typicallymapped to a Diamond Plot, which is a graphical representation of thediamond's surface used for recording the type and position of each flawor inclusion. Today, inspecting, plotting and mapping the diamond flawsis a manual process requiring a human expert gemologist.

Inclusions may appear as bright or dark spots on an image of the diamondwhen viewed under a microscope. Typically, a micro-lens setup can beused to capture high resolution digital images of the diamonds includingany bright spots or dark spots. It is noted that the typical inspectionand grading is carried out with a microscope having a predeterminedstandard magnification, such as, for example, 10×. Furthermore, any onediamond may have inclusions or imperfections that may not be visibleduring the standard inspection and grading process. Thus the inspectionand grading process is limited to those imperfections or inclusionswhich are visible or recognizable under the standard inspection process.

It may be advantageous to have a system capable of creating athree-dimensional computer generated model of a gemstone, such as adiamond, from one or more of the following inputs: a set of two-dimensional images, metrics including crown angle, pavilion angle, tablesize, cutlet size, star length, lower-girdle length, girdle thickness,girdle facets, camera metrics, lighting metrics and other to bedetermined information needed to generate the model. The computergenerated three-dimensional model may emulate realistic lightingconditions. Machine learning analysis of the image data may be used togenerate the computer rendered model and inclusion locations may bedetermined from analyzing the image data inputs. In various embodimentsof the present invention, a manual inclusion map may be generated duringa machine learning training period. The inclusions may be mapped on thegenerated model and displayed to a user.

The present invention relates generally to the field of gemologicalanalysis, and more particularly to mapping gemological features. One wayto map gemological features may include image data analysis in order todetermine the location of inclusions in the gemstone. Embodiments bywhich to analyze image data in order to determine the location ofinclusions in the gemstone are described in detail below by referring tothe accompanying drawings FIGS. 1-4. Although embodiments of the presentinvention are directed at mapping gemological features of gemstonesgenerally, for exemplary purposes only, the following description isdirected at mapping and encoding gemological features of diamondsspecifically. FIG. 1 depicts a functional block diagram illustrating adistributed data processing environment, generally designated 100, inaccordance with one embodiment of the present invention. The distributeddata processing environment 100 may include server 110, user device 120,imaging system 130 all connected via network 140.

Server 110 and user device 120 may be a laptop computer, tabletcomputer, netbook computer, personal computer (PC), a desktop computer,a smart phone, or any programmable electronic device capable ofcommunicating with various components and devices distributed dataprocessing environment 100, for example, server 110, user device 120,and imaging system 130, via network 140. In various embodiments, server110 may be a separate server or series of servers, a database, or otherdata storage, internal or external to user device 120 and imaging system130.

In various embodiments, user device 120 may act generally to host anapplication capable of display, in a graphical user interface, orcommunicate over a network, for example network 140, via a web browser.In various embodiments of the invention, user device 120 may communicatewith other computing devices within distributed data processingenvironment 100. User device 120 may communicate requests over network140 for, for example, a request for a digital fingerprint oridentification of a mineral crystal, or diamond, fingerprint generatedby server 110 based on image data received by server 110 from imagingsystem 130.

Imaging system 130 can be lens-based system, video system, or any systemcapable of generating image data and communicating the generated imagedata to other devices, for example, server 110 and user device 120 overnetwork 140.

In various embodiments, server 110 includes inclusion mappingapplication 111, as described in more detail below with reference toFIG. 2. Inclusion mapping application 111 may act generally to receive aset of image data, for example, from imaging system 130 via server 110.Inclusion mapping application 111 may analyze the received image data ofdiamonds and utilize computer vision algorithms and machine learningparameters to derive the locations of inclusions or defects based on thereceived image data. Inclusion mapping application 111 may map thesurface of the diamond and generate a 3D model of the diamond based onthe image data that includes the identified inclusions.

In an alternate embodiment of the present invention, imaging system 130may include mapping application 111 in a data storage device and theinvention presented below may be conducted within imaging system 130.

Additionally, in an alternate embodiment of the present invention, userdevice 120 may include a lensing system for capturing image data and adata store that includes inclusion mapping application 111, in order toperform the functions of server 110 and imaging system 130.

FIG. 2 depicts a functional block diagram illustrating the components ofinclusion mapping application 111 on server 110, within the distributeddata processing environment 100, in accordance with an embodiment of thepresent invention. Inclusion mapping application 111 includes receivingmodule 200, inclusion identification module 210, mapping module 220,encoding module 230, and fingerprint generation module 240.

In reference to FIGS. 1 and 2, receiving module 200 may receive requestsfor diamond digital fingerprints and sets of image data, for example,from user device 120 and imaging system 130 respectively. Receivingmodule 200 may identify any metadata associated with the receive imagedata in order to determine the resolution and magnification factor ofthe image data. In various embodiments, the resolution and magnificationvalues captured by imaging system 130 may be predetermined, for example,image data captured by imaging system 130 may have a resolution of1920×1080 pixels and a magnification factor of 10×. Receiving module 200may communicate the received image data and associated metadata toinclusion identification module 210. The image data may represent ameasurement of visible light reflected from the surface of theassociated mineral crystal or diamond. It should be appreciated that thereflected visible light is meant to be electromagnetic radiation at awavelength of 400 nm to 700 nm.

Inclusion identification module 210 may receive image data fromreceiving module 200. Inclusion identification module 210 may analyzethe received image data in order to identify inclusions or defects inthe diamond based on the image data. Inclusion identification module 210may use machine learning or computer vision segmentation in order topartition the received image data into multiple segments. In variousembodiments, segmentation uses a grid layer on the received image andwhich allows for the identification of objects with boundaries within animage. Inclusion identification module 210 may determine that theidentified objects or boundaries represent inclusions within thediamond.

In various embodiments, inclusion identification module 210 may generatea three-dimensional model based on the received image data usingrasterization. Rasterization is the description of an image in a vectorgraphics format and converting it into a raster image for output on avideo display or printer, for example, a display on user device 120. Invarious embodiments, the raster image may be produced in real-time asthree-dimensional renderings of received image data. Ray tracing may beused for the received still image data rendering. Ray tracing is arendering technique for generating an image by tracing the path of lightas pixels in an image plane and simulating the effects of its encounterswith virtual objects. It may be advantageous to use ray tracing withdiamond images as ray tracing is capable of simulating reflection andrefraction, scattering, and dispersion phenomena, for example, chromaticaberrations.

The model may include lighting conditions by applying rasterization orray tracing to the model based on the received image data. The surfaceof the diamond and internal inclusions may be included in the modelusing the segmentation analysis and identifying inclusion as non-linearisolated areas on the diamond surface. In various embodiments, inclusionidentification module 210 may communicate the model data to mappingmodule 220.

Mapping module 220 may receive diamond model data from inclusionidentification module 210 that includes surface data and inclusion data.Mapping module 220 may map the inclusions identified by inclusionidentification module 210 on to a tree structure representing thetwo-dimensional surface of the diamond at a configurable magnification.

Encoding module 230 may receive mapped inclusions from mapping module220 and encode the inclusions using Freeman's chain-code algorithm. Thealgorithm may calculate the radial distance associated with the mappedinclusions by calculating a contour of an inclusion by tracing in adirection, or direction vector, e.g., counterclockwise, beginning with aselected starting point, or reference vector, and each contour step iscomputed and stored. Particularly, starting from the reference vector,the distance between the center of mass and the contour is measured indefined angular steps and plotted as a function of the polar angle. Thethree-dimensional precise encoding of the three-dimensional defect,generated in this manner from an embodiment may provide increasedefficiency in defining inclusions in the diamonds as compared topresently available approximate sketches of a two-dimensional outline ofan inclusion based on human observation of the gem under a microscope.

FIG. 6 depicts an exemplary diagram of a Freeman's chain-code, generallydesignated 600 and an exemplary diagram of chain-coding, designatedchain-code 610. Freeman's chain-code 600 represents the value associatedwith the direction of movement in chain-code 610. In variousembodiments, chain-code 610 starts in the shaded block above the blackblock and the value of the direction of each of the subsequent contoursteps may be stored.

exemplary contour of Freeman's chain-code 600 is tracedcounter-clockwise, beginning with the line shaded point in the top rowand the direction of each of the subsequent contour steps is stored.

Chain code and radial distance algorithms. A chain code is a losslesscompression algorithm for monochrome images. The basic principle ofchain codes is to separately encode each connected component, oridentified inclusion, in the image. For each such region, a point on theboundary is selected and its coordinates are transmitted. Encodingmodule 230 may move along the boundary of the region and, at each step,transmits direction of this movement. The three-dimensional preciseencoding of the three-dimensional defect, generated in this manner froman embodiment may improve the defining of the defect in the diamond ascompared to presently available approximate sketches of atwo-dimensional outlines of defects based on human observation of thegem under a microscope.

Fingerprint generation module 240 may generate a digital fingerprintbased received image data, the mapped inclusions, and encodedinclusions. The generated fingerprint may include metadata tags thatassociate the fingerprint with the mineral crystal, or diamond, that wascaptured in the image data.

FIG. 3 depicts a flowchart depicting operational steps of inclusionmapping application 111, on server 110 within the data processingenvironment 100 of FIG. 1, in accordance with an embodiment of thepresent invention.

Receiving module 200 receives a set of image data (block 300), forexample, from imaging system 130, via server 110. In variousembodiments, receiving module 200 receives image data from user device120 with an associated request for a mineral crystal fingerprint.Receiving module 200 communicates the received image data to inclusionidentification module 210.

Inclusion identification module 210 analyzes the received image data(block 310). Inclusion identification module 210 analyzes the image databy segmentation of the received image data. In various embodiments,inclusion identification module 210 generates a three-dimensional modelof the diamond associated with the image based on receivedtwo-dimensional image data. Inclusion identification module 210 rotateseach image of the set of image data such that the surface of each imageis perpendicular to a viewing plane. Inclusion identification module 210projects the surface of the two-dimensional image onto the viewing planegenerating a two-dimensional rendering of the image. Inclusionidentification module 210 generates a three-dimensional model of thediamond surface based on the projected set of two-dimensionalrenderings.

Inclusion identification module 210 identifies inclusions based on theanalyzed image data (block 320), In various embodiments, inclusionidentification module 210 identifies the inclusions as non-linearisolated regions on the generated surface of the diamond model.Inclusion identification module 210 communicates the identifiedinclusions to mapping module 220.

Mapping module 220 receives identified inclusions from inclusionidentification module 210 and maps the identified inclusions to a treestructure (block 330). The mapped tree structure generated by mappingmodule 220 represents the identified inclusions on the surface of thediamond where the magnification is configurable for optimal encoding.Mapping module 220 communicates the mapped inclusions and magnificationto encoding module 230.

Encoding module 230 encodes the received mapped inclusions (block 340)as a chain-code associated with the diamond. Encoding module 230calculates the radial distance of the mapped inclusions (block 350) as atraced contour, in a direction, for example, counterclockwise, of theboundaries of the inclusion. The contour begins with a selected startingpoint, and each contour step is computed and stored. In variousembodiments, encoding module 230, starts from the reference direction,and calculates the distance between the center of mass of the diamondand the center of mass of the mapped inclusions, where the contour ismeasured in defined angular steps and plotted as a function of the polarangle. Encoding module 230 communicates the mapped inclusions and theencoded inclusions to fingerprint generation module 240.

Fingerprint generation module 240 generates a fingerprint associatedwith the diamond captured by the image data based on the received imagedata, mapped inclusions, and encoded inclusions (block 360).

The defects called inclusions in diamonds predominantly determine theirgrading. They look as bright or dark spots in diamond microscope images.Some examples of such defects are shown in FIG. 4, described below. Amicro-lens setup, for example, imaging system 130 can be used to obtainhigh resolution images of diamonds and their inclusions.

FIG. 4 depicts an illustrative block flow diagram of the analysis,mapping, and encoding of image data in accordance with an embodiment ofthe present invention. With reference to FIGS. 1, 2, and 4, receivingmodule 200 may receive a set of image data associated with a diamond. Animage in the set of images (block 400) may be communicated to inclusionidentification module 210 for analysis.

In various embodiments, inclusion identification module 210 segmentsreceived image data (block 410) and a segment (block 420) is enlargedfor inclusion identification. The image segmentation may be implementedusing machine learning parameters or computer vision techniques. Imagesegmentation is the process of partitioning a digital image intomultiple segments (sets of pixels, also known as super-pixels). The goalof segmentation is to simplify and/or change the representation of animage for more efficient analysis. In various embodiments, imagesegmentation may be performed using convolutional neural networks whereinclusion types are classified using machine learning classifiers. Imagesegmentation may allow the 3D position of inclusions to be determinedbased on 3D reconstruction from multiple segmented input images. Imagesegmentation is typically used to locate objects and boundaries (lines,curves, etc.) in images. More precisely, image segmentation is theprocess of assigning a label to every pixel in an image such that pixelswith the same label share certain characteristics. The result of imagesegmentation is a set of segments that collectively cover the entireimage, or a set of contours extracted from the image. Each of the pixelsin a region are similar with respect to some characteristic or computedproperty, such as color, intensity, or texture. Adjacent regions aresignificantly different with respect to the same characteristic(s).

In various embodiments, non-linear isolated regions are identified andthe identified inclusion region mapped and encoded using chain-code(block 430). In various embodiments, each segment of the segmented imageis analyzed and inclusions are identified, mapped, and encoded.Fingerprint generation module 240 may generate a diamond fingerprint(block 440) based on the image data and identified, mapped, and encodedinclusions.

FIG. 5 depicts a block diagram of components of server 110 and othercomponents of distributed data processing environment 100 of FIG. 1, forexample, user device 120, in accordance with an embodiment of thepresent invention. It should be appreciated that FIG. 5 provides only anillustration of one implementation and does not imply any limitationswith regard to the environments in which different embodiments may beimplemented. Many modifications to the depicted environment may be made.

Server 110 may include one or more processors 502, one or morecomputer-readable RAMs 504, one or more computer-readable ROMs 506, oneor more computer readable storage media 508, device drivers 512,read/write drive or interface 514, network adapter or interface 516, allinterconnected over a communications fabric 518. Communications fabric518 may be implemented with any architecture designed for passing dataand/or control information between processors (such as microprocessors,communications and network processors, etc.), system memory, peripheraldevices, and any other hardware components within a system.

One or more operating systems 510, and one or more application programs511, for example, genetic classification application 111, are stored onone or more of the computer readable storage media 508 for execution byone or more of the processors 502 via one or more of the respective RAMs504 (which typically include cache memory). In the illustratedembodiment, each of the computer readable storage media 508 may be amagnetic disk storage device of an internal hard drive, CD-ROM, DVD,memory stick, magnetic tape, magnetic disk, optical disk, asemiconductor storage device such as RAM, ROM, EPROM, flash memory orany other computer-readable tangible storage device that can store acomputer program and digital information.

Server 110 may also include an R/W drive or interface 514 to read fromand write to one or more portable computer readable storage media 526.Application programs 511 on server 110 may be stored on one or more ofthe portable computer readable storage media 526, read via therespective R/W drive or interface 514 and loaded into the respectivecomputer readable storage media 508.

Server 110 may also include a network adapter or interface 516, such asa TCP/IP adapter card or wireless communication adapter (such as a 4Gwireless communication adapter using OFDMA technology) for connection toa network 517. Application programs 511 on Server 110 may be downloadedto the computing device from an external computer or external storagedevice via a network (for example, the Internet, a local area network orother wide area network or wireless network) and network adapter orinterface 516. From the network adapter or interface 516, the programsmay be loaded onto computer readable storage media 508. The network maycomprise copper wires, optical fibers, wireless transmission, routers,firewalls, switches, gateway computers and/or edge servers.

Server 110 may also include a display screen 520, a keyboard or keypad522, and a computer mouse or touchpad 524. Device drivers 512 interfaceto display screen 520 for imaging, to keyboard or keypad 522, tocomputer mouse or touchpad 524, and/or to display screen 520 forpressure sensing of alphanumeric character entry and user selections.The device drivers 512, R/W drive or interface 514 and network adapteror interface 516 may comprise hardware and software (stored on computerreadable storage media 508 and/or ROM 506).

The present invention may be a system, a method, and/or a computerprogram product at any possible technical detail level of integration.The computer program product may include a computer readable storagemedium (or media) having computer readable program instructions thereonfor causing a processor to carry out aspects of the present invention.

The computer readable storage medium can be a tangible device that canretain and store instructions for use by an instruction executiondevice. The computer readable storage medium may be, for example, but isnot limited to, an electronic storage device, a magnetic storage device,an optical storage device, an electromagnetic storage device, asemiconductor storage device, or any suitable combination of theforegoing. A non-exhaustive list of more specific examples of thecomputer readable storage medium includes the following: a portablecomputer diskette, a hard disk, a random access memory (RAM), aread-only memory (ROM), an erasable programmable read-only memory (EPROMor Flash memory), a static random access memory (SRAM), a portablecompact disc read-only memory (CD-ROM), a digital versatile disk (DVD),a memory stick, a floppy disk, a mechanically encoded device such aspunch-cards or raised structures in a groove having instructionsrecorded thereon, and any suitable combination of the foregoing. Acomputer readable storage medium, as used herein, is not to be construedas being transitory signals per se, such as radio waves or other freelypropagating electromagnetic waves, electromagnetic waves propagatingthrough a waveguide or other transmission media (e.g., light pulsespassing through a fiber-optic cable), or electrical signals transmittedthrough a wire.

Computer readable program instructions described herein can bedownloaded to respective computing/processing devices from a computerreadable storage medium or to an external computer or external storagedevice via a network, for example, the Internet, a local area network, awide area network and/or a wireless network. The network may comprisecopper transmission cables, optical transmission fibers, wirelesstransmission, routers, firewalls, switches, gateway computers and/oredge servers. A network adapter card or network interface in eachcomputing/processing device receives computer readable programinstructions from the network and forwards the computer readable programinstructions for storage in a computer readable storage medium withinthe respective computing/processing device.

Computer readable program instructions for carrying out operations ofthe present invention may be assembler instructions,instruction-set-architecture (ISA) instructions, machine instructions,machine dependent instructions, microcode, firmware instructions,state-setting data, configuration data for integrated circuitry, oreither source code or object code written in any combination of one ormore programming languages, including an object oriented programminglanguage such as Smalltalk, C++, or the like, and procedural programminglanguages, such as the “C” programming language or similar programminglanguages. The computer readable program instructions may executeentirely on the user's computer, partly on the user's computer, as astand-alone software package, partly on the user's computer and partlyon a remote computer or entirely on the remote computer or server. Inthe latter scenario, the remote computer may be connected to the user'scomputer through any type of network, including a local area network(LAN) or a wide area network (WAN), or the connection may be made to anexternal computer (for example, through the Internet using an InternetService Provider). In some embodiments, electronic circuitry including,for example, programmable logic circuitry, field-programmable gatearrays (FPGA), or programmable logic arrays (PLA) may execute thecomputer readable program instructions by utilizing state information ofthe computer readable program instructions to personalize the electroniccircuitry, in order to perform aspects of the present invention.

Aspects of the present invention are described herein with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems), and computer program products according to embodiments of theinvention. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer readable program instructions.

These computer readable program instructions may be provided to aprocessor of a general-purpose computer, special purpose computer, orother programmable data processing apparatus to produce a machine, suchthat the instructions, which execute via the processor of the computeror other programmable data processing apparatus, create means forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks. These computer readable program instructionsmay also be stored in a computer readable storage medium that can directa computer, a programmable data processing apparatus, and/or otherdevices to function in a particular manner, such that the computerreadable storage medium having instructions stored therein comprises anarticle of manufacture including instructions which implement aspects ofthe function/act specified in the flowchart and/or block diagram blockor blocks.

The computer readable program instructions may also be loaded onto acomputer, other programmable data processing apparatus, or other deviceto cause a series of operational steps to be performed on the computer,other programmable apparatus or other device to produce a computerimplemented process, such that the instructions which execute on thecomputer, other programmable apparatus, or other device implement thefunctions/acts specified in the flowchart and/or block diagram block orblocks.

The flowchart and block diagrams in the Figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods, and computer program products according to variousembodiments of the present invention. In this regard, each block in theflowchart or block diagrams may represent a module, segment, or portionof instructions, which comprises one or more executable instructions forimplementing the specified logical function(s). In some alternativeimplementations, the functions noted in the blocks may occur out of theorder noted in the Figures. For example, two blocks shown in successionmay, in fact, be executed substantially concurrently, or the blocks maysometimes be executed in the reverse order, depending upon thefunctionality involved. It will also be noted that each block of theblock diagrams and/or flowchart illustration, and combinations of blocksin the block diagrams and/or flowchart illustration, can be implementedby special purpose hardware-based systems that perform the specifiedfunctions or acts or carry out combinations of special purpose hardwareand computer instructions.

The programs described herein are identified based upon the applicationfor which they are implemented in a specific embodiment of theinvention. However, it should be appreciated that any particular programnomenclature herein is used merely for convenience, and thus theinvention should not be limited to use solely in any specificapplication identified and/or implied by such nomenclature. Based on theforegoing, a computer system, method, and computer program product havebeen disclosed. However, numerous modifications and substitutions can bemade without deviating from the scope of the present invention.Therefore, the present invention has been disclosed by way of exampleand not limitation.

What is claimed is:
 1. A method for mapping one or more inclusions in amineral crystal, the method comprising: receiving a set of image dataassociated with the mineral crystal; analyzing the received set of imagedata, wherein analyzing the received set of image data further comprisessegmenting the set of image data via machine learned parameters;identifying one or more inclusions associated with the mineral crystalbased on the analyzed image data, wherein inclusions are non-linearisolated regions on a surface of the mineral crystal; mapping theidentified one or more inclusions of the mineral crystal to a treestructure representing the surface of the mineral crystal; encoding themapped one or more inclusions as a chain-code associated with themineral crystal; calculating a radial distance between a center of massvalue of the mineral crystal and a center of mass value of theidentified one or more inclusions; and generating a mineral crystalfingerprint, wherein the mineral crystal fingerprint is based on atleast the encoded one or more inclusions and the calculated radialdistance.
 2. The method of claim 1, wherein the set of image datafurther comprises at least one of: two-dimensional pictorial data;three-dimensional model data; and video data.
 3. The method of claim 1,wherein encoding the mapped one or more inclusions further comprises:plotting the radial distance as a function of a polar angle relative tothe center of mass value of the identified one or more inclusions. 4.The method of claim 1, wherein the set of image data is formatted basedon a predetermined resolution value and magnification value.
 5. Themethod of claim 1, wherein the set of image data represents ameasurement of visible light reflected from the surface associated withthe mineral crystal, wherein a wavelength associated with themeasurement of visible light is 400 nm-700 nm.
 6. The method of claim 1,wherein generating a mineral crystal fingerprint further comprises:determining a set of contours associated with the one or moreinclusions, wherein each contour of the set of contours include at leasta direction vector and a reference vector; calculating a contour angleassociated a difference value between the direction vector and thereference vector; and storing the calculated contour angle in a datastore.
 7. The method of claim 1, wherein analyzing the received set ofimage data further comprises: rotating each image of the set of imagedata such that a surface each image is perpendicular to a viewing plane;projecting on the surface a set of two-dimensional renderings on theimage; and generating a three-dimensional model based on the projectedset of two-dimensional renderings.
 8. A computer program product formapping one or more inclusions in a mineral crystal, the computerprogram product comprising: one or more computer-readable storage mediaand program instructions stored on the one or more computer-readablestorage media, the program instructions comprising: instructions toreceive a set of image data associated with the mineral crystal;instructions to analyze the received set of image data, whereininstructions to analyze the received set of image data further comprisesinstructions to segment the set of image data via machine learnedparameters; instructions to identify one or more inclusions associatedwith the mineral crystal based on the analyzed image data, whereininclusions are non-linear isolated regions on a surface of the mineralcrystal; instructions to map the identified one or more inclusions ofthe mineral crystal to a tree structure representing the surface of themineral crystal; instructions to encode the mapped one or moreinclusions as a chain-code associated with the mineral crystal;instructions to calculate a radial distance between a center of massvalue of the mineral crystal and a center of mass value of theidentified one or more inclusions; and instructions to generate amineral crystal fingerprint, wherein the mineral crystal fingerprint isbased on at least the encoded one or more inclusions and the calculatedradial distance.
 9. The computer program product of claim 8, wherein theset of image data further comprises at least one of: two-dimensionalpictorial data; three-dimensional model data; and video data.
 10. Thecomputer program product of claim 8, wherein instructions to encode themapped one or more inclusions further comprises: instructions to plotthe radial distance as a function of a polar angle relative to thecenter of mass value of the identified one or more inclusions.
 11. Thecomputer program product of claim 8, wherein the set of image data isformatted based on a predetermined resolution value and magnificationvalue.
 12. The computer program product of claim 8, wherein the set ofimage data represents a measurement of visible light reflected from thesurface associated with the mineral crystal, wherein a wavelengthassociated with the measurement of visible light is 400 nm-700 nm. 13.The computer program product of claim 8, wherein instructions togenerate a mineral crystal fingerprint further comprises: instructionsto determine a set of contours associated with the one or moreinclusions, wherein each contour of the set of contours include at leasta direction vector and a reference vector; instructions to calculate acontour angle associated a difference value between the direction vectorand the reference vector; and instructions to store the calculatedcontour angle in a data store.
 14. The computer program product of claim8, wherein instructions to analyze the received set of image datafurther comprises: instructions to rotate each image of the set of imagedata such that a surface each image is perpendicular to a viewing plane;instructions to project on the surface a set of two-dimensionalrenderings on the image; and instructions to generate athree-dimensional model based on the projected set of two-dimensionalrenderings.
 15. A computer system for mapping one or more inclusions ina mineral crystal, the computer system comprising: one or more computerprocessors; one or more computer-readable storage media; programinstructions stored on the computer-readable storage media for executionby at least one of the one or more processors, the program instructionscomprising: instructions to receive a set of image data associated withthe mineral crystal; instructions to analyze the received set of imagedata, wherein instructions to analyze the received set of image datafurther comprises instructions to segment the set of image data viamachine learned parameters; instructions to identify one or moreinclusions associated with the mineral crystal based on the analyzedimage data, wherein inclusions are non-linear isolated regions on asurface of the mineral crystal; instructions to map the identified oneor more inclusions of the mineral crystal to a tree structurerepresenting the surface of the mineral crystal; instructions to encodethe mapped one or more inclusions as a chain-code associated with themineral crystal; instructions to calculate a radial distance between acenter of mass value of the mineral crystal and a center of mass valueof the identified one or more inclusions; and instructions to generate amineral crystal fingerprint, wherein the mineral crystal fingerprint isbased on at least the encoded one or more inclusions and the calculatedradial distance.
 16. The computer system of claim 15, wherein the set ofimage data further comprises at least one of: two-dimensional pictorialdata; three-dimensional model data; and video data.
 17. The computersystem of claim 15, wherein instructions to encode the mapped one ormore inclusions further comprises: instructions to plot the radialdistance as a function of a polar angle relative to the center of massvalue of the identified one or more inclusions.
 18. The computer systemof claim 15, wherein the set of image data represents a measurement ofvisible light reflected from the surface associated with the mineralcrystal, wherein a wavelength associated with the measurement of visiblelight is 400 nm-700 nm.
 19. The computer system of claim 15, whereininstructions to generate a mineral crystal fingerprint furthercomprises: instructions to determine a set of contours associated withthe one or more inclusions, wherein each contour of the set of contoursinclude at least a direction vector and a reference vector; instructionsto calculate a contour angle associated a difference value between thedirection vector and the reference vector; and instructions to store thecalculated contour angle in a data store.
 20. The computer system ofclaim 15, wherein instructions to analyze the received set of image datafurther comprises: instructions to rotate each image of the set of imagedata such that a surface each image is perpendicular to a viewing plane;instructions to project on the surface a set of two-dimensionalrenderings on the image; and instructions to generate athree-dimensional model based on the projected set of two-dimensionalrenderings.